2020 SINAPSE ASM Jun 19, 2020 09:00 AM - 05:00 PM — Virtual Meeting (online)
3rd International Conference on Medical Imaging with Deep Learning Jul 06, 2020 - Jul 08, 2020 — Virtual Meeting (online)
Medical Image Understanding and Analysis Conference 2020 Jul 15, 2020 - Jul 17, 2020 — Virtual Meeting (online)
CAFACHEM 2020 Summer School on Organic & Halogen Radiochemistry Aug 25, 2020 - Aug 28, 2020 — KCL Waterloo Campus, London
Scottish Dementia Research Consortium Annual Conference 2020 [rescheduled] Sep 07, 2020 10:00 AM - 04:00 PM — Radisson Blu, 301 Argyle St, Glasgow

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

SINAPSE Image of the Month: fMRI predictors of cognitive behavioural therapy response

October 2019 SINAPSE Image of the Month

October2019

Courtesy of Dr Filippo Queirazza, this image shows weight maps from a feature selection step in multivariate analysis of fMRI data acquired from participants with depression performing a probabilistic reversal-learning task. After the fMRI scanning session, participants engaged in an online self-help programme based on cognitive behavioural therapy (CBT). Approximately half of the participants were classified as responders to treatment, based upon reduction in clinical depression inventory score upon completing the intervention. Multivariate classification of pretreatment fMRI contrast images produced the results shown above, identifying right amygdala (A) and right striatum (B) as the most discriminative features to classify individual response to treatment. Thus, pretreatment activation in those brain regions while acquiring and processing feedback information during probabilistic learning offers significant classification of participants who subsequently respond or do not respond to CBT. The results suggest this fMRI task activation holds the potential to be adopted as a predictive biomarker of response to CBT in depression.

 

The image is taken from a recent study published in Science Advances:

Queirazza F, Fouragnan E, Steele JD, Cavanagh J, Philiastides MG. Neural correlates of weighted reward prediction error during reinforcement learning classify response to cognitive behavioral therapy in depression. Sci Adv 2019; 5(7): eaav4962.